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A robustness information and visualization model for time and space assembly line balancing under uncertain demand

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  • Chica, Manuel
  • Cordón, Óscar
  • Damas, Sergio
  • Bautista, Joaquín

Abstract

The time and space assembly line balancing problem (TSALBP) is a realistic multiobjective version of assembly line balancing industrial problems involving the joint optimization of conflicting criteria such as the cycle time, the number of stations, and the area of these stations. However, the existing problem formulation does not consider the industrial scenario where the demand of a set of mixed products is variable and uncertain. In this work we propose to introduce novel robustness functions to measure how robust the line configuration is when the production plans demand changes. These functions are based on the stations overload under future demand conditions and are used as additional a posteriori information for the non-dominated solutions found by any multiobjective optimization method. The values of the robustness functions are put together with a novel graphical representation to form a generic model that aims to offer a better picture of the robustness of the set of Pareto-optimal solutions.

Suggested Citation

  • Chica, Manuel & Cordón, Óscar & Damas, Sergio & Bautista, Joaquín, 2013. "A robustness information and visualization model for time and space assembly line balancing under uncertain demand," International Journal of Production Economics, Elsevier, vol. 145(2), pages 761-772.
  • Handle: RePEc:eee:proeco:v:145:y:2013:i:2:p:761-772
    DOI: 10.1016/j.ijpe.2013.05.030
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Lai, Tsung-Chyan & Sotskov, Yuri N. & Dolgui, Alexandre, 2019. "The stability radius of an optimal line balance with maximum efficiency for a simple assembly line," European Journal of Operational Research, Elsevier, vol. 274(2), pages 466-481.
    2. Boysen, Nils & Schulze, Philipp & Scholl, Armin, 2022. "Assembly line balancing: What happened in the last fifteen years?," European Journal of Operational Research, Elsevier, vol. 301(3), pages 797-814.
    3. Manuel Chica & Joaquín Bautista & Jesica de Armas, 2019. "Benefits of robust multiobjective optimization for flexible automotive assembly line balancing," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 75-103, March.
    4. Bentaha, Mohand Lounes & Battaïa, Olga & Dolgui, Alexandre & Hu, S. Jack, 2015. "Second order conic approximation for disassembly line design with joint probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 247(3), pages 957-967.
    5. Dutta, Debprotim & Bose, Indranil, 2015. "Managing a Big Data project: The case of Ramco Cements Limited," International Journal of Production Economics, Elsevier, vol. 165(C), pages 293-306.
    6. Chica, Manuel & Bautista, Joaquín & Cordón, Óscar & Damas, Sergio, 2016. "A multiobjective model and evolutionary algorithms for robust time and space assembly line balancing under uncertain demand," Omega, Elsevier, vol. 58(C), pages 55-68.
    7. Lai, Tsung-Chyan & Sotskov, Yuri N. & Dolgui, Alexandre & Zatsiupa, Aksana, 2016. "Stability radii of optimal assembly line balances with a fixed workstation set," International Journal of Production Economics, Elsevier, vol. 182(C), pages 356-371.
    8. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).

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